[1]韩崇,孙力娟,肖甫,等.基于SVD的无线多媒体传感器网络图像压缩机制[J].东南大学学报(自然科学版),2012,42(5):814-819.[doi:10.3969/j.issn.1001-0505.2012.05.004]
　Han Chong,Sun Lijuan,Xiao Fu,et al.Image compression scheme in wireless multimedia sensor networks based on SVD[J].Journal of Southeast University (Natural Science Edition),2012,42(5):814-819.[doi:10.3969/j.issn.1001-0505.2012.05.004]
点击复制

基于SVD的无线多媒体传感器网络图像压缩机制()
分享到：

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
42
期数:
2012年第5期
页码:
814-819
栏目:
计算机科学与工程
出版日期:
2012-09-20

文章信息/Info

Title:
Image compression scheme in wireless multimedia sensor networks based on SVD
作者:
韩崇1;  孙力娟1; 2;  肖甫1; 2; 3;  郭剑1; 2;  王汝传1; 2; 3
1 南京邮电大学计算机学院, 南京 210003; 2 南京邮电大学江苏省无线传感网高技术研究重点实验室, 南京 210003; 3 苏州大学江苏省计算机信息处理技术重点实验室, 苏州 215006
Author(s):
Han Chong1;  Sun Lijuan1; 2;  Xiao Fu1; 2; 3;  Guo Jian1; 2;  Wang Ruchuan1; 2; 3
1 College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2 Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing University of Posts and Telecommunications, Nanjing 210003, China
3 Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou 215006, China
关键词:
无线多媒体传感器网络;  图像压缩;  奇异值分解;  节点协作
Keywords:
wireless multimedia sensor networks;  image compression;  singular value decomposition;  node collaboration
分类号:
TP393
DOI:
10.3969/j.issn.1001-0505.2012.05.004
摘要:
针对无线多媒体传感器网络图像压缩问题,从节点协作特性出发,提出了一种基于奇异值分解的图像压缩传输方案.首先研究了基于SVD的分块图像自适应压缩算法,以平衡网络能耗为目标,将相机节点和普通节点按照角色分工,协作完成图像采集、压缩和传输工作.相机节点负责采集图像信息,然后将图像分块发送给簇内普通节点; 簇内普通节点对分块图像进行自适应压缩并将数据发送给簇头节点; 簇头节点再将压缩后的数据转发至基站.仿真结果表明,提出的网络拓扑方案和图像压缩传输机制极大地缓解了图像采集节点的能耗压力,有效地平衡了网络的节点能耗.与JPEG2000协同图像压缩方案相比,基于SVD的图像处理方案的网络总能耗更少; 且后者能够有效地对图像进行压缩传输,平衡网络能耗,延长整个网络的生命周期.
Abstract:
Aiming at the issue of image compression in wireless multimedia sensor networks, starting from the node collaboration features, an image compression and transmission scheme based on singular value decomposition(SVD)is proposed. First, an adaptive blocking image compression algorithm based on SVD is studied. To balance the energy consumption of the network, according to the roles division, camera nodes and common nodes are cooperated to accomplish the workload of image acquisition, compression and transmission. Camera nodes gather images and send blocking images to the common nodes in cluster. Common nodes adaptively compress the partitioned images and send the compressed data to the cluster head node. Then, the cluster head node sends the compressed image data to the station. Simulation results show that the energy consumption pressure of camera nodes is greatly released by the proposed image compression and network topology scheme, and the network energy consumption is effectively balanced. Compared with the JPEG2000 collaborative image compression scheme, the total network energy consumption of the proposed cooperative image processing scheme based on SVD is less. In addition, the proposed scheme can effectively compress and transmit images, balance the energy consumption of network and prolong the life of the whole network.

参考文献/References:

[1] Akyildiz I F,Melodia T,Chowdhury K R.A survey on wireless multimedia sensor networks [J].Computer Networks,2007,51(4):921-960.
[2] 罗武胜,翟永平,鲁琴.无线多媒体传感器网络研究[J].电子与信息学报,2008,30(6):1511-1516.
　 Luo Wusheng,Zhai Yongping,Lu Qin.Study on wireless multimedia sensor networks [J].Journal of Electronics and Information Technology,2008,30(6):1511-1516.(in Chinese)
[3] Wu H M,Abouzeid A A.Energy-efficient distributed image compression in resource-constrained multihop wireless networks [J].Computer Communications,2005,28(14):1658-1668.
[4] Lu Q,Luo W S,Wang J D,et al.Low-complexity and energy efficient image compression scheme for wireless sensor networks [J].Computer Networks,2008,52(13):2594-2603.
[5] Lu Q,Luo W S,Ye X B.Collaborative in-network processing of LT based image compression algorithm in WMSNs [C] //Proceeding of the 1st International Workshop on Education Technology and Computer Science.Wuhan,China,2009:839-843.
[6] 鲁琴,罗武胜,胡冰.无线传感网基于邻居簇的JPEG2000多节点协同实现[J].光学精密工程,2010,18(1):240-247.
　 Lu Qin,Luo Wusheng,Hu Bing.Multi-node cooperative JPEG2000 implementation based on neighbor clusters in wireless sensor networks [J].Optice and Precision Engineering,2010,18(1):240-247.(in Chinese)
[7] Huu P N,Tran-Quang V,Miyoshi T.Low-complexity and energy-efficient algorithms on image compression for wireless sensor networks [J].IEICE Transactions on Communications,2010,E93-B(12):3438-3447.
[8] Andrews H C,Patterson C L.Singular value decomposition(SVD)image coding [J].IEEE Transactions on Communications,1976,24(4):425-432.
[9] Ranade A,Mahabalaro S S,Kale S.A variation on SVD based image compression [J].Image and Vision Computing,2007,25(6):771-777.
[10] Golub G H,Reinsch C.Singular value decomposition and least squares solutions [J].Numerische Mathematik,1970,14(5):403-420.
[11] Heinzelman W R,Chandrakasan A,Balakrishnan H.Energy-efficient communication protocol for wireless microsensor networks [C] //Proceeding of the 33rd Annual Hawaii International Conference on System Sciences.Washington DC,USA:IEEE Press,2000:3005-3014.
[12] Wang A,Chandrakasan A.Energy-efficient DSPs for wireless sensor networks [J].IEEE Signal Processing Magazine,2002,19(4):68-78.

相似文献/References:

[1]沈昱,高敏麟,孙小菡,等.采用光纤网络的工业多媒体通信研究[J].东南大学学报(自然科学版),1999,29(1):119.[doi:10.3969/j.issn.1001-0505.1999.01.025]
　Shen Yu,Gao Minlin,Sun Xiaohan,et al.Research of Industrial Multimedia Communication on Optic Fiber Network[J].Journal of Southeast University (Natural Science Edition),1999,29(5):119.[doi:10.3969/j.issn.1001-0505.1999.01.025]

备注/Memo

备注/Memo:
作者简介: 韩崇(1985—),男,博士生; 孙力娟(联系人),女,博士,教授,博士生导师,sunlj@njupt.edu.cn.
基金项目: 国家自然科学基金资助项目(60973139, 61003236, 61170065, 61171053)、教育部博士点基金资助项目(20103223120007, 20113223110002)、江苏省自然科学基金资助项目(BK2011755)、江苏省科技支撑计划资助项目(BE2010197, BE2010198)、江苏省普通高校自然科学研究计划资助项目(11KJA520001, 11KJB520016)、江苏省普通高校研究生科研创新计划资助项目(CX10B_200Z, CXZZ12_0480, CXZZ12_0481).
引文格式: 韩崇,孙力娟,肖甫,等.基于SVD的无线多媒体传感器网络图像压缩机制[J].东南大学学报:自然科学版,2012,42(5):814-819. [doi:10.3969/j.issn.1001-0505.2012.05.004]
更新日期/Last Update: 2012-09-20